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	title        = {Issues on Quality Assessment of SNOMED CT® Subsets - Term Validation and Term Extraction},
	abstract     = {The aim of this paper is to apply and develop methods based
on Natural Language Processing for automatically testing the
validity, reliability and coverage of various Swedish
SNOMED-CT subsets, the Systematized NOmenclature of
MEDicine - Clinical Terms a multiaxial, hierarchical
classification system which is currently being translated from
English to Swedish. Our work has been developed across two
dimensions. Initially a Swedish electronic text collection of
scientific medical documents has been collected and
processed to a uniform format. Secondly, a term processing
activity has been taken place. In the first phase of this activity,
various SNOMED CT subsets have been mapped to the text
collection for evaluating the validity and reliability of the
translated terms. In parallel, a large number of term
candidates have been extracted from the corpus in order to
examine the coverage of SNOMED CT. Term candidates that
are currently not included in the Swedish SNOMED CT can
be either parts of compounds, parts of potential multiword
terms, terms that are not yet been translated or potentially new
candidates. In order to achieve these goals a number of
automatic term recognition algorithms have been applied to
the corpus. The results of the later process is to be reviewed
by domain experts (relevant to the subsets extracted) through
a relevant interface who can decide whether a new set of
terms can be incorporated in the Swedish translation of
SNOMED CT or not.
	journal      = {Proceedings of RANLP-2009 Workshop: Biomedical Information Extraction.},
	author       = {Kokkinakis, Dimitrios and Gerdin, Ulla},
	year         = {2009},